ECON423 - Exam 2

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probit(h) sharet c trated # autos by truck=

# autos by truck=prob truck%*#total auto shipped

df for F statistic

# restrictions and n-k

LRTS (likelihood ratio test statistic)

-2(Lr-Lu)=-2(-210--205)=-2(5)=-10

firms.est(h) cost? @ c q? # of independent period fixed effects

0 because (xxx) does not contain per=f

Phi(-2.58) Phi(2.58)

0.5% 99.5%

# of slope coefficients for bivariate

1

firms.est(h,cx=f,per=f) cost? @ q? # of intercepts

1

15 observations of 10 states dimensions of u

150 (15x10) by 1

15 observations of 10 states dimensions of cov(u)

150 x 150

z=-1 z=1

16% 84%

Phi(-1.96) Phi(1.96)

2.5% 97.5%

firms.est(h,cx=f,per=f) cost? @ q? # of independent cross section fixed effects

3 (4 firms - 1)

firms.est(h,cx=f,per=f) cost? @ q? # of slope coefficients

4 (one for each firm)

Phi(-1.645) Phi(1.645)

5% 95%

Phi(0)

50%

truck/rail price difference of zero, # autos shipped by truck=

50% of total because z=0 => Phi(0)=50%

firms.est(xxx) COST? Q? yrII yrIII @ c geometry

6 parallel lines

firms.est(h,cx=f,per=f) cost? @ q? # of independent period fixed effects

9 (10 years - 1)

EViews log likelihood

@Logl

wald statement for truck/rail price difference of zero

@cnorm(c(1))=0.5

ls(h) approved c white female female/male difference in white/black difference = 0% coincidence? why or why not?

NO Because coefficient of interacted dummy variable=0 NB white/black issue has been fixed here

trated

Truck rate - Rail rate

xxxx.est(h) Y? X? @ C label c(i)

X? c(1) C c(2), c(3)

probit(h) call_back c female EViews expression to test Ho that female-male difference is zero

[@cnorm(c(1)+c(2))]-[@cnorm(c(1))]=0

fixed effects estimated intercept

average of separate estimated intercepts

firms.est(xxx) COST? Q? yrII yrIII @ c C (intercept)

average of the averages in each row

LRTS distribution

chi squared

we associate @covariance with

coefficient covariance matrix

cx=f

cross section fixed effects sum to zero

firms.est(xxx) COST? Q? yrII yrIII @ c c(4) =

firm A @ yrI (table)

firms.est(xxx) COST? Q? yrII yrIII @ c c(5) =

firm B @ yrI (table)

fixed effects c--XXX

fixed effects estimated intercept+c--XXX=separate estimated intercepts

Estimated intercept for cx=f,per=f

intercept+cross fixed effects+period fixed effects

firms.est(xxx) COST? Q? yrII yrIII @ c c(4) is the _____ for firm ____ in year ____

intercept, A, 1

countries.est(h) yb? b? g? @ c int_us=48 int_can=48 countries.est(h, cx=f) yb? b? g? intercept reported on EViews c--US c--CAN

intercept=48 c--US=0 c--CAN=0

15 observations of 10 states dimensions of @COVARIANCE

k x k

firms.est(h,cx=f,per=f) cost? @ q? k=?

k=(# of intercepts)+(# of slope coefficients)+(# of independent cross section fixed effects)+(# of independent period fixed effects)=17

k

number of regressors

per=f

period fixed effects sum to zero

probit(h) sharet c trated prob truck%=

prob truck%=phi(z_hat)

firms.est(xxx) COST? Q? yrII yrIII @ c is c(1) the marginal cost?

yes

probit(h) call_back c female c(1)=a1 c(2)=a2 ahat1+ahat2=0 (y,n)

yes

firms.est(xxx) COST? Q? yrII yrIII @ c c(2) =

yrII-yrI

firms.est(xxx) COST? Q? yrII yrIII @ c c(3) =

yrIII-yrI

probit(h) sharet c trated z_hat=

z_hat=c(1)+c(2)*trated

probit(h) sharet c trated ΔP=

ΔP=Δtrated

arc-slope

ΔQ/ΔP


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